Translational genomics in personalized medicine – scientific challenges en route to clinical practice

Background

In the area of omics and translational bio(medical)sciences, there is an increasing need to integrate, normalize, analyze, store and protect genomics data. Large datasets and scientific knowledge are rationally combined into valuable clinical information that ultimately will benefit human healthcare and are en route to clinical practice. Data from biomarker discovery and Next Generation Sequencing (NGS) are very valuable and will combine in comprehensive analyses to stratify medicine and guide therapy planning and ultimately benefit patients. However, the combination into useful and applicable information and knowledge is not trivial.

NGS in personalized medicine

Personalized medicine generally promises to result in both higher quality in treatment for individual patients and in lower costs in health care since patients will be offered only such therapies that are more effective for them and treatments that will not be safe or effective will be avoided. Recent advancements in biomedical and genomic sciences have paved the way to translate such research into clinical practice and health policies. However, the move towards greater personalization of medicine also comes along with challenges in the development of novel diagnostic and therapeutic tools in a complex framework that assumes that the use of genomic information is part of a translational continuum, which spans from basic to clinical research, preclinical and clinical trials, to policy research and the analysis of health and economic outcomes. The use of next-generation genomic technologies to improve the quality of life and efficiency of healthcare delivered to patients has become a mainstay theme in the field as benefits derived from such approaches include reducing a patient’s need to go through ineffective therapies, lowering side- and off-target effects of drugs, prescribing prophylactic therapies before acute exacerbations, and reducing expenditures.

Economic challenges

As such, personalized medicine promises to increase the quality of clinical care and, in some cases, to decrease health care costs. Besides the scientific challenges, there are several economic hurdles. For instance, healthcare providers need to know, whether the approach of personalized healthcare is affordable and worth the expenses. In addition, the economic rationale of personalized healthcare includes not only the reduction of the high expense of hospitalizations, the predictive diagnostics that will help to reduce cost through prevention or the increased efficacy of personalized therapies needs to offset prices of drugs. There are also several factors that influence payer adoption, coverage and reimbursement; the strength of evidence drives payers‘ decisions about coverage and reimbursement, varies widely depending on the personalized healthcare technology applied and regulation and cost-effectiveness seem to be increasingly associated with reimbursement, which is strongly influenced by professional society guidelines. In general, we see the following main obstacles to the advancement of personalized medicine: (i) the scientific challenges (a poor understanding of molecular mechanisms or a lack of molecular markers associated with some diseases, for example), (ii) the economic challenges (poorly aligned incentives), and (iii) operational issues in public healthcare systems. The operational issues can often be largely resolved within a particular stakeholder group, but correcting the incentive structure and modifying the relationships between stakeholders is more complex.

En route to clinical practice

This article focuses on the scientific difficulties that remain to translate genomics technologies into clinical practice and reviews recent technological advances in genomics and the challenges and potential benefits of translating this knowledge into clinical practice, with a particular focus on their applications in oncology.

Electronic supplementary material

The online version of this article (doi:10.1186/1877-6566-6-2) contains supplementary material, which is available to authorized users.     

Personalized diagnostics and biosensors: a review of the biology and technology needed for personalized medicine

Abstract

Exploiting the burgeoning fields of genomics, proteomics and metabolomics improves understanding of human physiology and, critically, the mutations that signal disease susceptibility. Through these emerging fields, rational design approaches to diagnosis, drug development and ultimately personalized medicine are possible. Personalized medicine and point-of-care testing techniques must fulfill a host of constraints for real-world applicability. Point-of-care devices (POCDs) must ultimately provide a cost-effective alternative to expensive and time-consuming laboratory tests in order to assist health care personnel with disease diagnosis and treatment decisions. Sensor technologies are also expanding beyond the more traditional classes of biomarkers – nucleic acids and proteins – to metabolites and direct detection of pathogens, ultimately increasing the palette of available techniques for the use of personalized medicine. The technologies needed to perform such diagnostics have also been rapidly evolving, with each generation being increasingly sensitive and selective while being more resource conscious. Ultimately, the final hurdle for all such technologies is to be able to drive consumer adoption and achieve a meaningful medical outcome for the patient.     

An economic perspective on personalized medicine

The concept of personalized medicine not only promises to enhance the life of patients and increase the quality of clinical practice and targeted care pathways, but also to lower overall healthcare costs through early-detection, prevention, accurate risk assessments and efficiencies in care delivery. Current inefficiencies are widely regarded as substantial enough to have a significant impact on the economies of major nations like the US and China, and, therefore the world economy. A recent OECD report estimates healthcare expenditure for some of the developed western and eastern nations to be anywhere from 10% to 18%, and growing (with the US at the highest). Personalized medicine aims to use state-of-the-art genomic technologies, rich medical record data, tissue and blood banks and clinical knowledge that will allow clinicians and payors to tailor treatments to individuals, thereby greatly reducing the costs of ineffective therapies incurred through the current trial and error clinical paradigm. Pivotal to the field are drugs that have been designed to target a specific molecular pathway that has gone wrong and results in a diseased condition and the diagnostic tests that allow clinicians to separate responders from non-responders. However, the truly personalized approach in medicine faces two major problems: complex biology and complex economics; the pathways involved in diseases are quite often not well understood, and most targeted drugs are very expensive. As a result of all current efforts to translate the concepts of personalized healthcare into the clinic, personalized medicine becomes participatory and this implies patient decisions about their own health. Such a new paradigm requires powerful tools to handle significant amounts of personal information with the approach to be known as “P4 medicine”, that is predictive, preventive, personalized and participatory. P4 medicine promises to increase the quality of clinical care and treatments and will ultimately save costs. The greatest challenges are economic, not scientific.     

How the Electronic Health Record Will Change the Future of Health Care

Genetic testing is expected to play a critical role in patient care in the near future. Advances in genomic research have the potential to impact medicine in very tangible and direct ways, from carrier screening to disease diagnosis and prognosis to targeted treatments and personalized medicine. However, numerous barriers to widespread adoption of genetic testing continue to exist, and health information technology will be a critical means of addressing these challenges. Electronic health records (EHRs) are a digital replacement for the traditional paper-based patient chart designed to improve the quality of patient care. EHRs have become increasingly essential to managing the wealth of existing clinical information that now includes genetic information extracted from the patient genome. The EHR is capable of changing health care in the future by transforming the way physicians use genomic information in the practice of medicine.     

Personalized health care: from theory to practice

The practice of medicine stands at the threshold of a transformation from its current focus on the treatment of disease events to an emphasis on enhancing health, preventing disease and personalizing care to meet each individual's specific health needs. Personalized health care is a new and strategic approach that is driven by personalized health planning empowered by personalized medicine tools, which are facilitated by advances in science and technology. These tools improve the capability to predict health risks, to determine and quantify the dynamics of disease development, and to target therapeutic approaches to the needs of the individual. Personalized health care can be implemented today using currently available technologies and know-how and thereby provide a market for the rational introduction of new personalized medicine tools. The need for early adoption of personalized health care stems from the necessity to reduce the egregious and wasteful burden of preventable chronic diseases, which is not effectively addressed by our current approach to care.     

Breast cancer in the personal genomics era

Breast cancer is a heterogeneous disease with a complex etiology that develops from different cellular lineages, progresses along multiple molecular pathways, and demonstrates wide variability in response to treatment. The "standard of care" approach to breast cancer treatment in which all patients receive similar interventions is rapidly being replaced by personalized medicine, based on molecular characteristics of individual patients. Both inherited and somatic genomic variation is providing useful information for customizing treatment regimens for breast cancer to maximize efficacy and minimize adverse side effects. In this article, we review (1) hereditary breast cancer and current use of inherited susceptibility genes in patient management; (2) the potential of newly-identified breast cancer-susceptibility variants for improving risk assessment; (3) advantages and disadvantages of direct-to-consumer testing; (4) molecular characterization of sporadic breast cancer through immunohistochemistry and gene expression profiling and opportunities for personalized prognostics; and (5) pharmacogenomic influences on the effectiveness of current breast cancer treatments. Molecular genomics has the potential to revolutionize clinical practice and improve the lives of women with breast cancer.     

Ethical and legal aspects of oncogenomics

The discovery of the genes and cellular pathways that play fundamental roles in several diseases, and the understanding of many diseases at a molecular level due to the advances in the field of genomics, have revolutionized the diagnosis, therapy and prevention of human diseases. Application of genetic testing in numerous medical fields, including pharmacogenomics and oncogenomics, raised numerous ethical questions and introduced legal instruments that are aimed at ensuring the appropriate protection of human research participants. For the effective development of human genomics and translation of novel, validated biomarkers into potentially useful clinical applications in personalized medicine, there is a need for clear ethical standards and principles in all phases of clinical research.     

Dawn of ocular gene therapy: implications for molecular diagnosis in retinal disease

Personalized medicine aims to utilize genomic information about patients to tailor treatment. Gene replacement therapy for rare genetic disorders is perhaps the most extreme form of personalized medicine, in that the patients’ genome wholly determines their treatment regimen. Gene therapy for retinal disorders is poised to become a clinical reality. The eye is an optimal site for gene therapy due to the relative ease of precise vector delivery, immune system isolation, and availability for monitoring of any potential damage or side effects. Due to these advantages, clinical trials for gene therapy of retinal diseases are currently underway. A necessary precursor to such gene therapies is accurate molecular diagnosis of the mutation(s) underlying disease. In this review, we discuss the application of Next Generation Sequencing (NGS) to obtain such a diagnosis and identify disease causing genes, using retinal disorders as a case study. After reviewing ocular gene therapy, we discuss the application of NGS to the identification of novel Mendelian disease genes. We then compare current, array based mutation detection methods against next NGS-based methods in three retinal diseases: Leber’s Congenital Amaurosis, Retinitis Pigmentosa, and Stargardt’s disease. We conclude that next-generation sequencing based diagnosis offers several advantages over array based methods, including a higher rate of successful diagnosis and the ability to more deeply and efficiently assay a broad spectrum of mutations. However, the relative difficulty of interpreting sequence results and the development of standardized, reliable bioinformatic tools remain outstanding concerns. In this review, recent advances NGS based molecular diagnoses are discussed, as well as their implications for the development of personalized medicine.     

Pharmacogenetics and pharmacogenomics: role of mutational analysis in anti-cancer targeted therapy

The goal of cancer pharmacogenomics is to obtain benefit from personalized approaches of cancer treatment and prevention. Recent advances in genomic research have shed light on the crucial role of genetic variants, mainly involving genes encoding drug-metabolizing enzymes, drug transporters and targets, in driving different treatment responses among individuals, in terms of therapeutic efficacy and safety. Although a considerable amount of new targeted agents have been designed based on a finely understanding of molecular alterations in cancer, a wide gap between pharmacogenomic knowledge and clinical application still persists. This review focuses on the relevance of mutational analyses in predicting individual response to antitumor therapy, in order to improve the translational impact of genetic information on clinical practice.     

Paving the way for personalised behaviourally based prevention of obesity: systematic search of the literature

We have identified in the literature variants in 64 genes that may be involved in gene-obesity-behaviour interactions. Personalisation of behaviourally based preventive approaches against obesity seems feasible, however obesity genomics is still in the discovery phase of translational research and abundant replication studies are needed before these largely pioneering findings can be extended to practice and population impact. Automation of search algorithms and development of more efficient tools for knowledge synthesis of genomic research into gene-obesity-behaviour interactions might facilitate the advent of widely available personalised prevention approaches. Our future efforts shall therefore concentrate on developing such tools, as well as a research repository dedicated to the use of public health genomics for obesity control.     

Road-maps and revelations: on the somatic ethics of genetic susceptibility

Understanding genomic susceptibility risk has been represented as key to a new era of personalized medicine, in which “empowered” individuals shape their lives according to a “somatic ethics” of genetic risk management. Based on a comprehensive analysis of websites and other documents produced by key companies within the personal genomics industry, I argue that the rhetoric of empowerment these companies employ constructs an “ideal subject” of personal genomics while also expressing tensions implicit within the idea of a somatic ethics based on genetic susceptibility. Using Kaushik Sunder Rajan's concept of “genomic fetishism,” I show how these tensions arise from the relationship the rhetoric of personal genomics constructs between risk and uncertainty, and relate them to broader tensions within “risk thinking” as a mode of governmentality that extends beyond genomics.     

Personalized medicine: revolutionizing drug discovery and patient care.

Advances in human genome research are opening the door to a new paradigm for practising medicine that promises to transform healthcare. Personalized medicine, the use of marker-assisted diagnosis and targeted therapies derived from an individual's molecular profile, will impact the way drugs are developed and medicine is practiced. Knowledge of the molecular basis of disease will lead to novel target identification, toxicogenomic markers to screen compounds and improved selection of clinical trial patients, which will fundamentally change the pharmaceutical industry. The traditional linear process of drug discovery and development will be replaced by an integrated and heuristic approach. In addition, patient care will be revolutionized through the use of novel molecular predisposition, screening, diagnostic, prognostic, pharmacogenomic and monitoring markers. Although numerous challenges will need to be met to make personalized medicine a reality, with time, this approach will replace the traditional trial-and-error practice of medicine.     

Systems Approaches to Biology and Disease Enable Translational Systems Medicine

The development and application of systems strategies to biology and disease are transforming medical research and clinical practice in an unprecedented rate.In the foreseeable future,clinicians,medical researchers,and ultimately the consumers and patients will be increasingly equipped with a deluge of personal health information,e.g.,whole genome sequences,molecular profiling of diseased tissues,and periodic multi-analyte blood testing of biomarker panels for disease and wellness.The convergence of these practices will enable accurate prediction of disease susceptibility and early diagnosis for actionable preventive schema and personalized treatment regimes tailored to each individual.It will also entail proactive participation from all major stakeholders in the health care system.We are at the dawn of predictive,preventive,personalized,and participatory(P4) medicine,the fully implementation of which requires marrying basic and clinical researches through advanced systems thinking and the employment of high-throughput technologies in genomics,proteomics,nanofluidics,single-cell analysis,and computation strategies in a highly-orchestrated discipline we termed translational systems medicine.     

Predictive diagnostics and personalized medicine for the prevention of chronic degenerative diseases

Progressive increase of mean age and life expectancy in both industrialized and emerging societies parallels an increment of chronic degenerative diseases (CDD) such as cancer, cardiovascular, autoimmune or neurodegenerative diseases among the elderly. CDD are of complex diagnosis, difficult to treat and absorbing an increasing proportion in the health care budgets worldwide. However, recent development in modern medicine especially in genetics, proteomics, and informatics is leading to the discovery of biomarkers associated with different CDD that can be used as indicator of disease's risk in healthy subjects. Therefore, predictive medicine is merging and medical doctors may for the first time anticipate the deleterious effect of CDD and use markers to identify persons with high risk of developing a given CDD before the clinical manifestation of the diseases. This innovative approach may offer substantial advantages, since the promise of personalized medicine is to preserve individual health in people with high risk by starting early treatment or prevention protocols. The pathway is now open, however the road to an effective personalized medicine is still long, several (diagnostic) predictive instruments for different CDD are under development, some ethical issues have to be solved. Operative proposals for the heath care systems are now needed to verify potential benefits of predictive medicine in the clinical practice. In fact, predictive diagnostics, personalized medicine and personalized therapy have the potential of changing classical approaches of modern medicine to CDD.     

Cis-regulatory variation: significance in biomedicine and evolution

Cis-regulatory regions (CRR) control gene expression and chromatin modifications. Genetic variation at CRR in individuals across a population contributes to phenotypic differences of biomedical relevance. This standing variation is important for personalized genomic medicine as well as for adaptive evolution and speciation. This review focuses on genetic variation at CRR, its influence on chromatin, gene expression, and ultimately disease phenotypes. In addition, we summarize our understanding of how this variation may contribute to evolution. Recent technological and computational advances have accelerated research in the direction of personalized medicine, combining strengths of molecular biology and genomics. This will pave new ways to understand how CRR variation affects phenotypes and chart out possible avenues of intervention.